CNN经典论文-目录

1. LeNet：Gradient-Based Learning Applied to Document Recognition

2. AlexNet：ImageNet Classification with Deep Convolutional Neural Networks

3. VGG：Very Deep Convolutional Networks for Large-Scale Image Recognition, 2014.9

4. InceptionV1-V4：

1. Going Deeper withConvolutions，2014.9
2. Batch Normalization:Accelerating Deep Network Training by Reducing Internal Covariate Shift, 2015.2
3. Rethinking theInception Architecture for Computer Vision, 2015.12
4. Inception-v4,Inception-ResNet and the Impact of Residual Connections on Learning,2016.2

5. ResNet：Deep Residual Learning for Image Recognition, 2015.12

6. ResNeXt：Aggregated Residual Transformations for Deep Neural Networks, 2016.11

7. DenseNet：Densely Connected Convolutional Networks, 2016.8

8. SE-Net：Squeeze-and-Excitation Networks, 2017.9

9. EfficientNet：EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks, 2019.5

10. ResNeSt：ResNeSt: Split-Attention Networks, 2020.4